ValueError: After taking into account object store and redis memory usage, the amount of memory on this node available for tasks and actors (-0.01 GB) is less than 0% of total. You can adjust these settings with ray.init(memory=<bytes>, object store memory=<bytes>

What is the problem?

when i run ray in ML platform,

ValueError: After taking into account object store and redis memory usage, the amount of memory on this node available for tasks and actors (-0.01 GB) is less than 0% of total. You can adjust these settings with ray.init(memory=<bytes>, object store memory=<bytes>

occurs can you tell me the approximate value of memory size /object store memory i should set ? thanks

Ray version and other system information (Python version, TensorFlow version, OS):

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[chongxiaoc]

Any documentation about correctly initializing Ray inside a docker container? Hitting same issue here.

After upgrading to Ray 2.0, issue is gone on my side.

[rkooo567]

When you don’t specify the object store memory, it uses 20% of available memory. I think your machine doesn’t have enough available memory (20% of available memory is even less than 80MB).

You can manually specify object_store_memory to avoid this.

ray.init(object_store_memory=<bytes>)

the minimal you should specify is 78643200.

Better solution is to use an instance that has more available memory.